SoroushVahidi/scidocs huggingface dataset:
Food recognition using statistics of pairwise local features
(2010)

Food recognition is difficult because food items are de-formable objects that exhibit significant variations in appearance. We believe the key to recognizing food is to exploit the spatial relationships between different ingredients (such as meat and bread in a sandwich). We propose a new representation for food items that calculates pairwise statistics between local features computed over a soft pixel-level segmentation of the image into eight ingredient types. We accumulate these statistics in a multi-dimensional histogram, which is then used as a feature vector for a discriminative classifier. Our experiments show that the proposed representation is significantly more accurate at identifying food than existing methods.
A high-performance silicon-on-insulator MEMS gyroscope operating at atmospheric pressure
(2006)

This paper presents a new, high-performance silicon-on-insulator (SOI) MEMS gyroscope with decoupled oscillation modes. The gyroscope tructure allows it to achieve matched-resonance-frequencies, large drive-mode oscillation amplitude, high sense-mode quality factor, and low echanical cross-talk. The gyroscope is fabricated through the commercially available SOIMUMPS process of MEMSCAP Inc. The fabricated yroscope has minimum capacitive sense gaps of 2.6 m and a structural silicon thickness of 25 m, and it fits into a chip area smaller than mm × 3 mm. The fabricated gyroscope is hybrid connected to a CMOS capacitive interface ASIC chip, which is fabricated in a standard 0.6 m MOS process. The characterization of the hybrid-connected gyroscope demonstrates a low measured noise-equivalent rate of 90◦/h/Hz1/2 at tmospheric pressure, eliminating the need for a vacuum package for a number of applications. R2-non-linearity of the gyroscope is measured to e better than 0.02%. The gyroscope has a low quadrature signal of 70◦/s and a short-term bias stability of 1.5◦/s. The angular rate sensitivity of the yroscope is 100 V/(◦/s) at atmospheric pressure, which improves 24 times to 2.4 mV/(◦/s) at vacuum. The noise-equivalent rate of the gyroscope t 20 mTorr vacuum is measured to be 35◦/h/Hz1/2, which can be improved further by reducing the electromechanical noise. 2006 Elsevier B.V. All rights reserved.
A High-Efficiency Ultra-Low-Power CMOS Rectifier for RF Energy Harvesting Applications
(2018)

This paper presents a novel ultra-low power rectifier for RF energy harvester, designed and implemented in standard 130 nm CMOS technology. The proposed 915 MHz ISM band RF energy harvester is designed for wearable medical devices and internet of things (IoT) applications. An off-chip differential matching network passively boosts the low-level incoming AC signal generated by the antenna. Then, a novel self-compensated cross-coupled rectifier is designed to convert the AC signal into a DC output voltage. The rectifier is comprised of 10 stages and it uses both dynamic and static bias compensation to decrease the transistors forward voltage drop. The post-layout simulation results demonstrate a sensitivity of −30.5 dBm for 1 V output at a capacitive load which is lower than the current state-of-the-art. The peak end-to-end efficiency is 42.8 % at −16 dBm input power, delivering 2.32 V at 0.5 MΩ resistor load.
Relation Extraction with Matrix Factorization and Universal Schemas
(2013)

Traditional relation extraction predicts relations within some fixed and finite target schema. Machine learning approaches to this task require either manual annotation or, in the case of distant supervision, existing structured sources of the same schema. The need for existing datasets can be avoided by using a universal schema: the union of all involved schemas (surface form predicates as in OpenIE, and relations in the schemas of preexisting databases). This schema has an almost unlimited set of relations (due to surface forms), and supports integration with existing structured data (through the relation types of existing databases). To populate a database of such schema we present matrix factorization models that learn latent feature vectors for entity tuples and relations. We show that such latent models achieve substantially higher accuracy than a traditional classification approach. More importantly, by operating simultaneously on relations observed in text and in pre-existing structured DBs such as Freebase, we are able to reason about unstructured and structured data in mutually-supporting ways. By doing so our approach outperforms stateof-the-art distant supervision.
Benign violations: making immoral behavior funny.
(2010)

Humor is an important, ubiquitous phenomenon; however, seemingly disparate conditions seem to facilitate humor. We integrate these conditions by suggesting that laughter and amusement result from violations that are simultaneously seen as benign. We investigated three conditions that make a violation benign and thus humorous: (a) the presence of an alternative norm suggesting that the situation is acceptable, (b) weak commitment to the violated norm, and (c) psychological distance from the violation. We tested the benign-violation hypothesis in the domain of moral psychology, where there is a strong documented association between moral violations and negative emotions, particularly disgust. Five experimental studies show that benign moral violations tend to elicit laughter and amusement in addition to disgust. Furthermore, seeing a violation as both wrong and not wrong mediates behavioral displays of humor. Our account is consistent with evolutionary accounts of laughter, explains humor across many domains, and suggests that humor can accompany negative emotion.
An approach to discriminate GNSS spoofing from multipath fading
(2016)

GNSS signals are vulnerable to various types of interference including jamming and spoofing attacks. Spoofing signals are designed to deceive target GNSS receivers without being detected by conventional receiver quality monitoring metrics. This paper focuses on detecting an overlapped spoofing attack where the correlation peaks of the authentic and spoofing signals interact during the attack. Several spoofing detection and signal quality monitoring (SQM) metrics are introduced. This paper proposes a spoofing detection architecture utilizing combination of different metrics to detect spoofing signals and distinguish them from multipath signals. Experimental results show that the pre-despreading spoofing detection metrics such as variance analysis are not sensitive to multipath propagation and can be used in conjunction with post-despreading methods to correctly detect spoofing signals. Several test scenarios based on different spoofing and multipath cases are performed to demonstrate the effectiveness of the proposed architecture to correctly detect spoofing attack ands distinguish them from multipath.
PAST-TENSE GENERATION FROM FORM VERSUS MEANING: BEHAVIOURAL DATA AND SIMULATION EVIDENCE.
(2009)

The standard task used to study inflectional processing of verbs involves presentation of the stem form from which the participant is asked to generate the past tense. This task reveals a processing disadvantage for irregular relative to regular English verbs, more pronounced for lower-frequency items. Dual- and single-mechanism theories of inflectional morphology are both able to account for this pattern; but the models diverge in their predictions concerning the magnitude of the regularity effect expected when the task involves past-tense generation from meaning. In this study, we asked normal speakers to generate the past tense from either form (verb stem) or meaning (action picture). The robust regularity effect observed in the standard form condition was no longer reliable when participants were required to generate the past tense from meaning. This outcome would appear problematic for dual-mechanism theories to the extent that they assume the process of inflection requires stem retrieval. By contrast, it supports single-mechanism models that consider stem retrieval to be task-dependent. We present a single-mechanism model of verb inflection incorporating distributed phonological and semantic representations that reproduces this task-dependent pattern.
Deep Learning Approaches to Text Production
(2018)

Text production is a key component of many NLP applications. In data-driven approaches, it is used for instance, to generate dialogue turns from dialogue moves [Wen et al., 2015, Wen et al., 2016, Novikova et al., 2017], to verbalise the content of Knowledge bases [Gardent et al., 2017a, Gardent et al., 2017b] or to generate natural English sentences from rich linguistic representations, such as dependency trees [Belz et al., 2011, Mille et al., 2018] or Abstract Meaning Representations [May and Priyadarshi, 2017, Konstas et al., 2017, Song et al., ]. In text-driven methods on the other hand, text production is at work in sentence compression [Knight and Marcu, 2000, Cohn and Lapata, 2008, Filippova and Strube, 2008, Pitler, 2010, Filippova et al., 2015, Toutanova et al., 2016]; sentence fusion [McKeown et al., 2010, Filippova, 2010, Thadani and McKeown, 2013]; paraphrasing [Dras, 1999, Barzilay and McKeown, 2001, Bannard and Callison-Burch, 2005, Wubben et al., 2010, Narayan et al., 2016, Dong et al., 2017, Mallinson et al., 2017]; sentence (or text) simplification [Siddharthan et al., 2004, Zhu et al., 2010, Woodsend and Lapata, 2011, Wubben et al., 2012, Narayan and Gardent, 2014, Xu et al., 2015, Narayan and Gardent, 2016, Zhang and Lapata, 2017, Narayan et al., 2017], text summarisation [Wan, 2010, Nenkova and McKeown, 2011, Woodsend and Lapata, 2010, Rush et al., 2015, Cheng and Lapata, 2016, Nallapati et al., 2016, Chen et al., 2016, Tan and Wan, 2017, See et al., 2017, Nallapati et al., 2017, Paulus et al., 2017, Yasunaga et al., 2017, Narayan et al., 2018a, Narayan et al., 2018b, Pasunuru and Bansal, 2018, Celikyilmaz et al., 2018] and end-to-end dialogue systems [Li et al., 2017]. Following the success of encoder-decoder models in modeling sequence-rewriting tasks such as machine translation [Sutskever et al., 2011, Bahdanau et al., 2014], deep learning models have successfully been applied to the various text production tasks. For instance, [Rush et al., 2015] utilize a local attention-based model for abstractive summarisation, [Shang et al., 2015] propose an encoder-decoder model for response generation, [See et al., 2017] uses a hybrid of encoder-decoder model and pointer network [Vinyals et al., 2015] for story highlight generation, [Dong et al., 2017] exploits an encoder-decoder model for question rephrasing and [Konstas et al., 2017] for AMR generation. In this tutorial, we will cover the fundamentals and the state-of-the-art research on neural models for text production. Each text production task raises a slightly different communication goal (e.g, how to take the dialogue context into account when producing a dialogue turn; how to detect and merge relevant information when summarising a text; or how to produce a well-formed text that correctly capture the information contained in some input data in the case of data-to-text generation). We will outline the constraints specific to each subtasks and examine how the existing neural models account for them.
A Single-Stage Single-Switch LED Driver Based on Class-E Converter
(2016)

This paper proposes a single-stage single-switch light-emitting diode (LED) driver that integrates a buck-boost circuit with a Class-E resonant converter by sharing single-switch device. The buck-boost circuit, working as a power-factor correction (PFC) stage, operates in the discontinuous conduction mode (DCM) to shape the input current. The Class-E converter steps down the voltage to drive the LED. For specific component parameters, the Class-E converter can achieve soft-switching on the power switch and two rectifier diodes, and reduce switch losses at high frequencies. Electrolytic capacitors are used in the proposed converter to achieve a lower cost, but the system reliability decreases. To overcome this disadvantage, film capacitors can be used, but the current ripple increases. Neglecting the cost, multilayered film capacitors are the best option, if higher reliability and lower current ripple are required. The proposed driver features high efficiency (90.8%), and a high power factor (PF) (0.995). In this paper, analytical results and design considerations at 100 kHz are presented, and a 100-W prototype with 110 VAC input was built to validate the theoretical analysis.
Developing and validating an instrument for measuring user-perceived web quality
(2002)

Many of the instruments to measure information and system quality were developed in the context of mainframe and PC-based technologies of yesteryears. With the proliferation of the Internet and World Wide Web applications, users are increasingly interfacing and interacting with web-based applications. It is, therefore, important to develop new instruments and scales, which are directly targeted to these new interfaces and applications. In this article, we report on the development of an instrument that captures key characteristics of web site quality from the userâ€TMs perspective. The 25item instrument measures four dimensions of web quality: specific content, content quality, appearance and technical adequacy. While improvements are possible, the instrument exhibits excellent psychometric properties. The instrument would be useful to organizations and web designers as it provides an aggregate measure of web quality, and to researchers in related web research. a 1, b Purchase Export Previous article Next article Check if you have access through your login credentials or your institution.
An Implementation of Scoped Memory for Real-Time Java
(2001)

This paper presents our experience implementing the memory management extensions in the Real-Time Specification for Java. These extensions are designed to given real-time programmers the control they need to obtain predictable memory system behavior while preserving Java’s safe memory model. We describe our implementation of certain dynamic checks required by the Real-Time Java extensions. In particular, we describe how to perform these checks in a way that avoids harmful interactions between the garbage collector and the memory management system. We also found that extensive debugging support was necessary during the development of Real-Time Java programs. We therefore used a static analysis and a dynamic debugging package during the development of our benchmark applications.
Behavior-driven visualization recommendation
(2009)

We present a novel approach to visualization recommendation that monitors user behavior for implicit signals of user intent to provide more effective recommendation. This is in contrast to previous approaches which are either insensitive to user intent or require explicit, user specified task information. Our approach, called Behavior-Driven Visualization Recommendation (BDVR), consists of two distinct phases: (1) pattern detection, and (2) visualization recommendation. In the first phase, user behavior is analyzed dynamically to find semantically meaningful interaction patterns using a library of pattern definitions developed through observations of real-world visual analytic activity. In the second phase, our BDVR algorithm uses the detected patterns to infer a user's intended visual task. It then automatically suggests alternative visualizations that support the inferred visual task more directly than the user's current visualization. We present the details of BDVR and describe its implementation within our lab's prototype visual analysis system. We also present study results that demonstrate that our approach shortens task completion time and reduces error rates when compared to behavior-agnostic recommendation.
Small-signal analysis of closed-loop PWM boost converter in CCM with complex impedance load
(2016)

The following closed-loop transfer functions of the boost converter operating in continuous-conduction mode (CCM) supplying a complex impedance load are derived and analyzed: input-to-output voltage Mvcl and reference-to-output Tcl. The load of the boost dc-dc converter is composed of a series-connected resistance and inductance. The dynamic characteristics of the closed-loop boost converter with a third-order double-lead integral compensator are evaluated for different load inductances. The theoretically predicted results are validated through switching-circuit simulations using a suitable converter design example.
A 77-GHz FMCW MIMO Radar Based on an SiGe Single-Chip Transceiver
(2009)

This paper describes a novel frequency-modulated continuous-wave radar concept, where methods like nonuniform sparse antenna arrays and multiple-input multiple-output techniques are used to improve the angular resolution of the proposed system. To demonstrate the practical feasibility using standard production techniques, a prototype sensor using a novel four-channel single-chip radar transceiver in combination with differential patch antenna arrays was realized on off-the-shelf RF substrate. Furthermore, to demonstrate its practical applicability, the assembled system was tested in real world measurement scenarios in conjunction with the presented efficient signal processing algorithms.
An IQ-modulator based heterodyne 77-GHz FMCW colocated MIMO radar system
(2012)

In this work the realization of a 77-GHz frequency-division multiple-access-based frequency-modulated continuous-wave multiple-input multiple-output radar with four transceiver channels in conjunction with a non-uniform linear antenna array is presented. The radar system, consisting of an RF-frontend utilizes transceiver chips with integrated inphase/quadrature-modulators to generate the frequency shifted transmit signals and a field programmable gate array-based baseband board, is used for test measurements to verify the system performance and to demonstrate the beamforming capability as well as the accuracy of the digital-beamforming method.
MIMO radar theory and experimental results
(2004)

The continuing progress of Moore's law has enabled the development of radar systems that simultaneously transmit and receive multiple coded waveforms from multiple phase centers and to process them in ways that have been unavailable in the past. The signals available for processing from these multiple-input multiple-output (MIMO) radar systems appear as spatial samples corresponding to the convolution of the transmit and receive aperture phase centers. The samples provide the ability to excite and measure the channel that consists of the transmit/receive propagation paths, the target and incidental scattering or clutter. These signals may be processed and combined to form an adaptive coherent transmit beam, or to search an extended area with high resolution in a single dwell. Adaptively combining the received data provides the effect of adaptively controlling the transmit beamshape and the spatial extent provides improved track-while-scan accuracy. This paper describes the theory behind the improved surveillance radar performance and illustrates this with measurements from experimental MIMO radars.
Motion compensation and efficient array design for TDMA FMCW MIMO radar systems
(2012)

In this paper we present methods for the design of planar frequency-modulated continuous-wave (FMCW) multiple-input multiple-output (MIMO) arrays with an emphasis on the problem of moving targets in time-division multiple-access (TDMA) systems. We discuss the influence of target motion and boundaries of operation and present a method to compensate for its effects, which requires special attention in the array design and in signal processing. Array design techniques, examples including an implementation, and measurement results are also covered in this article.
An IQ-modulator based heterodyne 77-GHz FMCW radar
(2011)

In this paper a method to realize a heterodyne frequency-modulated continuous-wave (FMCW) radar is presented. The system operates at a frequency of 77 GHz and is based on an in-phase quadrature-phase (IQ) modulator in the transmit (TX)-path of the system. This IQ modulator is used as a single-sideband mixer, which allows the realization of an offset frequency between the radar's TX and receive signal. In this way it is possible to shift the frequency band containing the target information away from dc, which simplifies FMCW range measurement of targets close to the radar.
CP-nets: A Tool for Representing and Reasoning with Conditional Ceteris Paribus Preference Statements
(2004)

Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitative way. In this paper, we propose a qualitative graphical representation of preferences that reflects conditional dependence and independence of preference statements under a ceteris paribus (all else being equal) interpretation. Such a representation is often compact and arguably quite natural in many circumstances. We provide a formal semantics for this model, and describe how the structure of the network can be exploited in several inference tasks, such as determining whether one outcome dominates (is preferred to) another, ordering a set outcomes according to the preference relation, and constructing the best outcome subject to available evidence.
Fracking Sarcasm using Neural Network
(2016)

Precise semantic representation of a sentence and definitive information extraction are key steps in the accurate processing of sentence meaning, especially for figurative phenomena such as sarcasm, Irony, and metaphor cause literal meanings to be discounted and secondary or extended meanings to be intentionally profiled. Semantic modelling faces a new challenge in social media, because grammatical inaccuracy is commonplace yet many previous state-of-the-art methods exploit grammatical structure. For sarcasm detection over social media content, researchers so far have counted on Bag-of-Words(BOW), N-grams etc. In this paper, we propose a neural network semantic model for the task of sarcasm detection. We also review semantic modelling using Support Vector Machine (SVM) that employs constituency parsetrees fed and labeled with syntactic and semantic information. The proposed neural network model composed of Convolution Neural Network(CNN) and followed by a Long short term memory (LSTM) network and finally a Deep neural network(DNN). The proposed model outperforms state-of-the-art textbased methods for sarcasm detection, yielding an F-score of .92.
Empirical Power Computation Using SAS ® for Schuirmann ’ s Two One-Sided Tests Procedure in Clinical Pharmacokinetic Drug-Drug Interaction Studies
(2004)

Drug-drug interaction studies are becoming increasingly crucial in drug development. An FDA survey of recent new drug application submissions showed that 70% of drug-drug interaction studies were conducted using fixedsequence designs. Schuirmann’s Two One-sided Tests (TOST) procedure is the FDA preferred statistical method for evaluating drug-drug interaction. However, calculating the exact power of the TOST procedure generally requires sophisticated numerical integration. Monte Carlo simulation is a good alternative approach to the power calculation if a closed algerbraic formula is not available. This paper presents a SAS Macro to compute the empirical power of the TOST procedure under a fixed-sequence design. Empirical power curve plot and numerical table can be produced through this SAS macro.